checkmeanfilter

自己下载整理的层次分析法材料，相信对你会有用的。自己下载看下吧(Download finishing their AHP materials, that will be useful to you. Facie it yourself downloads)

《数字信号处理及其MATLAB实现》程序集(2004)( Digital signal processing and MATLAB to achieve the assembly (2004))

rls-dfeeq.m 均衡算法 用RLS-DFE算法实现(rls-dfeeq.m Equalization Algorithms with the RLS-DFE)

说明：  脑电信号特征提取 多尺度方法 经验模态分解 均值粗粒化 移动均值粗粒化(Feature Extraction of EEG Signals Multiscale method Empirical Mode Decomposition Mean coarsening Moving mean coarsening)

特征分解型求取离散分数阶傅里叶变换 特征分解算法通过求ＤＦＴ的核矩阵Ｆ（ｋ，ｎ）的特征值 和特征向量构造ＤＦＴ核矩阵的分数幂，以此作为Ｆａ（ｋ，ｎ） 来计算ＤＦｒＦＴ。(The kernel matrix eigenvalue decomposition algorithm for DFT F (k, n) characteristic value And the feature vectors are constructed as the fractional powers of the DFT kernel matrix, which are used as Fa (k, n) To calculate DFrFT.)

图象处理：计算连通域的面积、周长、圆形度、矩形度以及长宽比(Image processing: computing connected domain area, perimeter, roundness, and aspect ratio rectangular degree)

为了提高使用精度，研究了某型号MEMS陀螺仪的随机漂移模型。采用游程检验法分析了 该陀螺仪随机漂移数据的平稳性，并根据该漂移为均值非平稳、方差平稳的随机过程的结论， 采用梯度径向基（RBF）神经网络对漂移数据进行了建模。实验结果表明：相比经典RBF网络模 型而言，这种方法建立的模型能更好地描述MEMS陀螺仪的漂移特；相对于季节时间序列模型而 言，其补偿效果提高了大约15％。(In order to improve accuracy, to study a particular model of the MEMS gyroscope random drift model. Using run-length analysis of the test gyro random drift data stationarity, and in accordance with the drift for the average non-stationary, the variance of the random process a smooth conclusion, the use of gradient radial basis (RBF) neural network drift data to build mode. The experimental results show that: compared to the classical RBF network model, this method of establishing a model to better describe the MEMS gyroscope drift special compared with the seasonal time series model, the effect of their compensation increased by approximately 15.)

说明：  最近在研究脑电信号的处理 同事自己也收集了一些资料希望和大家分享(Recent studies dealing with EEG colleagues collected themselves would like to share some information)

Sheffield工具箱的简单例子，有作者修改，其中doc文件为介绍(the example of Sheffield GA)

用户提供样本数据后，对样本数据做c均值frm聚类分析。(c均值聚类)